Designed by Rob Tyrie
This is an experiment with the new llm from China called QWEN, which is available on the Hugging face platform.
The idea is to create a course outline with a simple prompt that is at The graduate certificate level which is 42 hours of education with outcomes connected to employment and cross training of people with undergrad degrees.
Is a great augmentation to marketing graduate certificates that are available in polytechnical institutions across North America.
This experiment took less than 10 minutes and it’s based on other courses that I have created for industry and for academia.
It’s an easy first draft and it really does provide the thinking material to design course course work that’s fairly standard.
It is obvious that based on this outline it’s also possible to start generating business case centered assignments and tests from the backbone of the class outline.
The big question is what you want to take this course or not. I do know that I can teach it, as long as I had a good co-pilot or 2 and some humans in the loop.
This is the experiment .
Course Title: Applied Generative AI for Business and Financial Analysts in Marketing, Finance, and Sales
Course Overview:
This 14-class postgraduate course is designed to equip business and financial analysts with the practical skills and knowledge necessary to leverage generative AI tools in their roles within marketing, finance, and sales departments. The course will focus on hands-on applications of AI tools and platforms, including ChatGPT, Gamma, Canvas, Julius.ai, SheetGPT, Claude.ai, Perplexity, Gemini, and Co-Pilots, to automate and enhance various business processes.
Course Objectives:
- Understand the practical applications of generative AI in marketing, finance, and sales.
- Learn how to use specific AI tools and platforms to enhance data analysis, decision-making, and strategic planning.
- Develop practical skills in automating tasks and workflows using AI.
- Gain insights into best practices and ethical considerations in AI deployment.
Course Structure:
The course will be delivered through a combination of lectures, hands-on workshops, case studies, guest speakers, and real-world projects. Each class will include interactive sessions and opportunities for students to apply what they have learned.
Class Schedule:
#### **Week 1: Introduction to Applied Generative AI**
- **Class 1: Course Overview and Introduction to Generative AI**
- Overview of the course structure and objectives.
- Introduction to generative AI: definition, types, and applications.
- Overview of AI tools and platforms: ChatGPT, Gamma, Canvas, Julius.ai, SheetGPT, Claude.ai, Perplexity, Gemini, and Co-Pilots.
#### **Week 2: Fundamentals of AI Tools**
- **Class 2: Introduction to ChatGPT and Claude.ai**
- Overview of ChatGPT and Claude.ai.
- Hands-on session: Setting up and using ChatGPT and Claude.ai for basic tasks.
- Case studies: ChatGPT and Claude.ai in customer service and content creation.
- **Class 3: Introduction to SheetGPT and Gemini**
- Overview of SheetGPT and Gemini.
- Hands-on session: Using SheetGPT for data analysis and Gemini for office automation.
- Case studies: SheetGPT and Gemini in financial modeling and report generation.
#### **Week 3: AI in Marketing**
- **Class 4: Using AI for Content Creation and Marketing Automation**
- Overview of AI tools for content creation: ChatGPT, Claude.ai, and Canvas.
- Hands-on session: Generating marketing content and automating social media posts.
- Case studies: AI-driven content creation and marketing campaigns.
- **Class 5: AI for Customer Segmentation and Personalization**
- Overview of AI tools for customer segmentation: ChatGPT, Gemini, and Co-Pilots.
- Hands-on session: Segmenting customers and personalizing marketing efforts.
- Case studies: AI in customer segmentation and personalized marketing.
#### **Week 4: AI in Finance**
- **Class 6: AI for Financial Analysis and Risk Management**
- Overview of AI tools for financial analysis: SheetGPT, ChatGPT, and Gemini.
- Hands-on session: Analyzing financial data and managing risk.
- Case studies: AI in fraud detection and credit scoring.
- **Class 7: AI for Investment and Portfolio Management**
- Overview of AI tools for investment: ChatGPT, Gemini, and Co-Pilots.
- Hands-on session: Developing investment strategies and optimizing portfolios.
- Case studies: AI in robo-advisors and algorithmic trading.
#### **Week 5: AI in Sales**
- **Class 8: AI for Sales Forecasting and Lead Generation**
- Overview of AI tools for sales forecasting: ChatGPT, Gemini, and Co-Pilots.
- Hands-on session: Predicting sales trends and generating leads.
- Case studies: AI in CRM and sales automation.
- **Class 9: AI for Customer Service and Support**
- Overview of AI tools for customer service: ChatGPT, Claude.ai, and Julius.ai.
- Hands-on session: Implementing chatbots and virtual assistants.
- Case studies: Improving customer satisfaction with AI.
#### **Week 6: Advanced AI Applications**
- **Class 10: AI for Voice Assistance and Avatars**
- Overview of AI tools for voice assistance: Claude.ai, Julius.ai, and Co-Pilots.
- Hands-on session: Creating voice assistants and avatars.
- Case studies: AI in customer service and virtual assistants.
- **Class 11: AI for Office Automation and Document Processing**
- Overview of AI tools for office automation: Perplexity, Gemini, and Co-Pilots.
- Hands-on session: Automating office tasks and document processing.
- Case studies: AI in document management and workflow automation.
#### **Week 7: Ethical Considerations and Best Practices**
- **Class 12: Ethical Considerations in AI Deployment**
- Overview of ethical issues in AI: bias, transparency, and accountability.
- Case studies: Ethical considerations in AI-driven decision-making.
- **Class 13: Best Practices for AI Implementation**
- Best practices for integrating AI into business processes.
- Case studies: Successful AI implementations in enterprise organizations.
- Hands-on session: Developing an AI implementation plan.
#### **Week 8: Final Project and Review**
- **Class 14: Final Project Presentations and Review**
- Students present their final projects, which involve using AI tools to solve a real-world business problem.
- Peer and instructor feedback.
- Course review and Q&A session.
### Assessment:
- **Participation and Engagement (20%)**: Active participation in class discussions, group activities, and online forums.
- **Assignments and Quizzes (30%)**: Weekly assignments and quizzes to reinforce learning.
- **Midterm Project (20%)**: A mid-term project where students apply AI tools to a real-world problem in marketing, finance, or sales.
- **Final Project (30%)**: A comprehensive final project that integrates all the concepts learned throughout the course. Students will present their projects to the class and receive feedback.
### Recommended Resources:
- **"AI for Business: A Practical Guide to Applying Artificial Intelligence in Your Organization" by Steven Finlay**
- **"Automate This: How Algorithms Came to Rule Our World" by Christopher Steiner**
- **Online Resources**: Official documentation and tutorials for ChatGPT, Gamma, Canvas, Julius.ai, SheetGPT, Claude.ai, Perplexity, Gemini, and Co-Pilots.
### Guest Speakers:
- Industry experts from leading companies in marketing, finance, and sales will be invited to share their experiences and insights on using generative AI tools in their respective fields.
### Prerequisites:
- Basic understanding of business and financial concepts.
- Familiarity with basic programming (Python preferred).
- Access to a computer with internet connectivity and the ability to install and use the specified AI tools.
Why take the program:
This course is designed to provide a practical and hands-on approach to using generative AI tools in marketing, finance, and sales. By the end of the course, students will be well-equipped to leverage AI to enhance their professional capabilities and drive innovation in their organizations.
This is the prop for the creation of the course outline, it’s in two sections:
Create an online for a 14 class postgraduate University course for business analysts and financial analysts that explore the use of generative AI in their jobs in marketing finance and sales departments.
This is an applied AI tools course. The focus is in the subject matter expertise of the analyst and the lessons are in using tools like Chatgpt, gamma, canvas , julius.ai, sheetGPT and claude.ai and other tools and platforms like perplexity, Gemini, co-pilots in office automation, voice assistance, avatars to get real work done in Enterprise organizations .
Rob Tyrie is a serial entrepreneur, who has founded it helps scale over a dozen software companies focused on Enterprise in highly complex sectors like government, military, insurance, Banking and Financial services. He started the screw as a programmer and it’s highly likely that he generated some code yesterday to prove a point or just to build out a delightful puzzle or game. He can be reached on LinkedIn pretty much 24 hours a day.
